Common Variability in the Stable Atmospheric Boundary Layer on Small Space and Time Scales

一个有规律的夜间发生是一个稳定的边界层的发展，这是一个浅，接近平静的空气层靠近地球表面。 然而，尽管空气看似平静，但仍有持续的运动对近地面温度和污染物的扩散产生重要影响。 该研究奖为分析现有的稳定边界层运动观测数据提供了支持，并重新审视了如何跟踪这些数据以及如何使用这些信息来改进数值天气模型。 该奖项将与当地的现场管理人员协商解决的一个具体用例是太平洋西北部的葡萄园，那里的霜冻和冻结有着显著的影响。该奖项下的研究将扩大对小尺度非平稳运动的理解，它们与表面异质性的相互作用，以及它们的随机行为。 重点是亚中尺度运动，其正式定义包括仅大于最大湍流涡旋的尺度上的运动，以及通常被认为是最小中尺度运动（2公里）的尺度上的运动。一系列不同类型的小规模运动的案例研究将使用来自9个先前的现场活动的数据和研究人员开发的一套不同的分析方法来构建。 该提案的主要目标是：1）量化温度、风矢量和湍流通量的亚中尺度时空变率，并将这些变率与强迫变量联系起来，2）跟踪数据网络中的传播模式，并检查它们与平缓地形引起的地表现象的相互作用，以及这种相互作用对湍流通量的影响，3）制定短期的概率分布（非湍流）的变化的温度和风向低风速和有关的特征分布的强迫变量，和4）重新分析基于时间平均法和基于该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

A regular nighttime occurrence is the development of a stable boundary layer, which is a shallow, near-calm layer of air near the Earth’s surface. However, despite the air seemingly being calm, there are ongoing motions which have important impacts on near-ground temperatures and the dispersion of pollutants. This research award provides support for the analysis of existing observational data on stable boundary layer motions, with a fresh look at how they can be tracked and how that information can be used to improve numerical weather models. A specific use case that this award will address, in consultation with local field managers, is vineyards in the Pacific Northwest where frosts and freezes have a significant impact.The research under this award will expand understanding of small-scale, non-stationary motions, their interaction with surface heterogeneity, and their stochastic behavior. The focus is on submeso motions, which are formally defined to include motions on scales just larger than the largest turbulent eddies and up to scales normally considered to be the smallest mesoscale motions (2km). A sequence of case studies of different types of small-scale motions will be constructed using data from 9 prior field campaigns and a package of different analysis methods that has been developed by the researcher. The main objectives of the proposal are to: 1) Quantify the submeso time and space variability of the temperature, the wind vector, and turbulent fluxes and relate these variations to the forcing variables, 2) Track propagating modes across networks of data and examine their interaction with surface-based phenomena due to gentle topography and the impact of this interaction on turbulent fluxes, 3) Formulate probability distributions for short-term (non-turbulent) variations of the temperature and wind direction for low wind speeds and relate the characteristics of the distributions to the forcing variables, and 4) Reanalyze the behavior of the fluxes and corresponding transfer coefficients in the bulk formula for low wind speeds based on time averaging and based on spatial averaging across the networks and improve formulation of the transfer coefficients for low wind speeds.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.